Methods for evaluating fracture patterns of polycrystalline materials based on the parameter analysis of fatigue striations: A review

Abstract

A review of the main literature sources was conducted, which made it possible to systematise various techniques, methods and software for studying the fracture mechanisms of polycrystalline materials. The principles of describing the patterns of failure surfaces based on multi-scale analysis (at the macro-, meso‑ and microlevels) were considered. Algorithms that recognize and calculate the parameters of fatigue striations on SEM images are analysed. They proved to be functional and capable of providing a valuable information and fractographic control.

Keywords: Algorithms; Fatigue striations; Fracture; Fracture patterns; Interpretation.

Graphical abstract

Fig. 1

Fatigue crack growth at the micro- (a), meso‑ (b) and macro- (c) levels [22].

Fig. 2

Automated analysis of fracture surface [40]: specimen cut out of the fracture surface – 1; fracture surfaces −2,3; image - 4, SEM −5; data transfer - 6 –; image analysis – 7; data processing −8.

Fig. 3

Scheme for describing the crack resistance of a polycrystalline specimen and corresponding scale levels that describe deformation and fracture processes.

Fig. 4

KDFF and FCG stages.

Fig. 5

Generalised ratio of the distances from fatigue striations S to the SIF range [43].

Fig. 6

Strain variation near the fatigue crack tip depending on the crack length and the number of load cycles [49].

Fig. 7

Scale levels (the macro-, meso‑ and micro- levels) of fractographic analysis and morphological elements of the fracture surface [56]: 1 - the total area of the specimen's fracture surface; 2 – individual fracture areas (grain conglomerates); 3 - localised microrelief formations.

Fig. 8

Structural fracture levels in FCG and their morphological formations.

Fig. 9

Classification of fatigue striations and parameters that describe their geometry.

Fig. 10

Diagram for measuring the geometry of fatigue striations (A) and a digital image analyser (B) used to measure the step (s) and height (h) of striations [84].

Fig. 11

Diagram of fractographic analysis - a and stereoscopic measurement - b of the surface morphology of a bimetallic 25Kh1M1F/15Kh13MF specimen (the direction of crack propagation is indicated by an arrow) [85].

Fig. 12

Primary (a) and secondary (b) images (at 0° and 20°) with identified points for measuring fatigue striations’ height.

Fig. 13

Results of stereoscopic height measurement (h) of fatigue striations of different widths (b) for databases B₁ and B₂. Designations of points are presented in Fig. 12b.

Fig. 14

The section of the fracture surface covered with fatigue striation and treated by phase demodulation [90].

Fig. 15

Example of automatic detection of striations: the upper image is a rough (rotated) SEM image, and the lower one shows the result of selecting fatigue striations [91].

Fig. 16

Typical fractographic image of the fatigue fracture surface of steel 34KhN3 M [93]:- marked with areas of analysis (a) - binary image obtained after iterative selection of local minima and the result of its morphological processing (b)- fragment of a binary image with the lines that correspond to the rotated bands (c).